{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "jqdatasdk not installed\n",
      "you are using non-interactive mdoel quantaxis\n"
     ]
    }
   ],
   "source": [
    "import QUANTAXIS as QA\n",
    "from QAPUBSUB.consumer import subscriber  # 消费者\n",
    "from QAPUBSUB.producer import publisher  # 生产者\n",
    "import threading  # 在线程中运行消费者，防止线程阻塞\n",
    "import json  # 消费者接收的数据是文本，转成json\n",
    "import pandas as pd  # json转成DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " prortfolio with user_cookie  USER_1m5xbkUB  already exist!!\n"
     ]
    }
   ],
   "source": [
    "# 1. 账户准备\n",
    "user = QA.QA_User(username='admin', password='admin')  # 账号密码跟81页面登录的账号密码一致\n",
    "# portfolio_cookie就像是组合的id\n",
    "port = user.new_portfolio(portfolio_cookie='x1')\n",
    "# account_cookie就像是账户的id，init_cash是账户的初始资金，market_type为市场类型，QA中通过market_type预设了交易规则，例如期货允许t0等，与国内的交易规则一致。\n",
    "acc = port.new_account(account_cookie='test_local_simpledeal', init_cash=100000, market_type=QA.MARKET_TYPE.FUTURE_CN)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2. 发单操作方法\n",
    "def sendorder(code, trade_price, trade_amount, trade_towards, trade_time):\n",
    "\tacc.receive_simpledeal(\n",
    "\t\tcode=code,\n",
    "\t\ttrade_price=trade_price,\n",
    "\t\ttrade_amount=trade_amount,\n",
    "\t\ttrade_towards=trade_towards,\n",
    "\t\ttrade_time=trade_time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 3. 策略\n",
    "market_data_list = []  # 存储历史数据\n",
    "# 下面订阅数据时会指定on_data为回调函数，接到数据就会执行on_data\n",
    "def on_data(a, b, c, data):\n",
    "    # 数据准备\n",
    "    bar = json.loads(data)\n",
    "    market_data_list.append(bar)\n",
    "    # 日线date格式是2019-01-01\n",
    "    market_data_df = pd.DataFrame(market_data_list).set_index('date', drop=False)\n",
    "\n",
    "    # 计算指标\n",
    "    ind = QA.QA_indicator_MA(market_data_df, 2, 4)  # 计算MA2和MA4\n",
    "    print(ind)\n",
    "    \n",
    "    # 策略逻辑\n",
    "    MA2 = ind.iloc[-1]['MA2']  # 取最新的MA2\n",
    "    MA4 = ind.iloc[-1]['MA4']  # 取最新的MA4\n",
    "    code = bar['code']  # 合约代码\n",
    "    trade_price = bar['close']  # 最新收盘价\n",
    "    trade_amount = 1  # 1手\n",
    "    trade_time = bar['date'] + ' 00:00:00'  # 由于日线date的格式是2019-01-01，所以要加后面的时间，否则无法计算指标，后面的问题章节有详细说明。\n",
    "    code_hold_available = acc.hold_available.get(code, 0)  # 合约目前的持仓情况\n",
    "    if MA2 > MA4:\n",
    "        if code_hold_available == 0:\n",
    "            print('买多')\n",
    "            sendorder(code, trade_price, trade_amount, QA.ORDER_DIRECTION.BUY_OPEN, trade_time)\n",
    "        elif code_hold_available > 0:\n",
    "            print('持有')\n",
    "        else:\n",
    "            print('平空')\n",
    "            sendorder(code, trade_price, trade_amount, QA.ORDER_DIRECTION.BUY_CLOSE, trade_time)\n",
    "    elif MA4 > MA2:\n",
    "        if code_hold_available == 0:\n",
    "            print('卖空')\n",
    "            sendorder(code, trade_price, trade_amount, QA.ORDER_DIRECTION.SELL_OPEN, trade_time)\n",
    "        elif code_hold_available < 0:\n",
    "            print('持有')\n",
    "        else:\n",
    "            print('平多')\n",
    "            sendorder(code, trade_price, trade_amount, QA.ORDER_DIRECTION.SELL_CLOSE, trade_time)\n",
    "    else:\n",
    "        print('不操作')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 4. 订阅数据\n",
    "sub = subscriber(exchange='x1')  # Exchange名为x1，在15672页面能看到\n",
    "sub.callback=on_data  # 指定回调函数\n",
    "threading.Thread(target=sub.start).start()  # 开线程执行订阅，防止线程阻塞，后面的发布代码无法执行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "QUANTAXIS>> Selecting the Best Server IP of TDX\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "USING DEFAULT STOCK IP\n",
      "USING DEFAULT FUTURE IP\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "QUANTAXIS>> === The BEST SERVER ===\n",
      " stock_ip 123.125.108.24 future_ip 59.175.238.38\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            MA2  MA4\n",
      "date                \n",
      "2019-08-01  NaN  NaN\n",
      "不操作\n",
      "               MA2  MA4\n",
      "date                   \n",
      "2019-08-01     NaN  NaN\n",
      "2019-08-02  3831.0  NaN\n",
      "不操作\n",
      "               MA2  MA4\n",
      "date                   \n",
      "2019-08-01     NaN  NaN\n",
      "2019-08-02  3831.0  NaN\n",
      "2019-08-05  3784.5  NaN\n",
      "不操作\n",
      "               MA2     MA4\n",
      "date                      \n",
      "2019-08-01     NaN     NaN\n",
      "2019-08-02  3831.0     NaN\n",
      "2019-08-05  3784.5     NaN\n",
      "2019-08-06  3730.0  3780.5\n",
      "卖空\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "持有\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "持有\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "持有\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "持有\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "平空\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "2019-08-14  3673.5  3653.75\n",
      "买多\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "2019-08-14  3673.5  3653.75\n",
      "2019-08-15  3692.5  3684.75\n",
      "持有\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "2019-08-14  3673.5  3653.75\n",
      "2019-08-15  3692.5  3684.75\n",
      "2019-08-16  3715.0  3694.25\n",
      "持有\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "2019-08-14  3673.5  3653.75\n",
      "2019-08-15  3692.5  3684.75\n",
      "2019-08-16  3715.0  3694.25\n",
      "2019-08-19  3731.0  3711.75\n",
      "持有\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "2019-08-14  3673.5  3653.75\n",
      "2019-08-15  3692.5  3684.75\n",
      "2019-08-16  3715.0  3694.25\n",
      "2019-08-19  3731.0  3711.75\n",
      "2019-08-20  3723.0  3719.00\n",
      "持有\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "2019-08-14  3673.5  3653.75\n",
      "2019-08-15  3692.5  3684.75\n",
      "2019-08-16  3715.0  3694.25\n",
      "2019-08-19  3731.0  3711.75\n",
      "2019-08-20  3723.0  3719.00\n",
      "2019-08-21  3692.5  3711.75\n",
      "平多\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "2019-08-14  3673.5  3653.75\n",
      "2019-08-15  3692.5  3684.75\n",
      "2019-08-16  3715.0  3694.25\n",
      "2019-08-19  3731.0  3711.75\n",
      "2019-08-20  3723.0  3719.00\n",
      "2019-08-21  3692.5  3711.75\n",
      "2019-08-22  3700.5  3711.75\n",
      "卖空\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "2019-08-14  3673.5  3653.75\n",
      "2019-08-15  3692.5  3684.75\n",
      "2019-08-16  3715.0  3694.25\n",
      "2019-08-19  3731.0  3711.75\n",
      "2019-08-20  3723.0  3719.00\n",
      "2019-08-21  3692.5  3711.75\n",
      "2019-08-22  3700.5  3711.75\n",
      "2019-08-23  3715.0  3703.75\n",
      "平空\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "2019-08-14  3673.5  3653.75\n",
      "2019-08-15  3692.5  3684.75\n",
      "2019-08-16  3715.0  3694.25\n",
      "2019-08-19  3731.0  3711.75\n",
      "2019-08-20  3723.0  3719.00\n",
      "2019-08-21  3692.5  3711.75\n",
      "2019-08-22  3700.5  3711.75\n",
      "2019-08-23  3715.0  3703.75\n",
      "2019-08-26  3543.5  3622.00\n",
      "卖空\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "2019-08-14  3673.5  3653.75\n",
      "2019-08-15  3692.5  3684.75\n",
      "2019-08-16  3715.0  3694.25\n",
      "2019-08-19  3731.0  3711.75\n",
      "2019-08-20  3723.0  3719.00\n",
      "2019-08-21  3692.5  3711.75\n",
      "2019-08-22  3700.5  3711.75\n",
      "2019-08-23  3715.0  3703.75\n",
      "2019-08-26  3543.5  3622.00\n",
      "2019-08-27  3326.5  3520.75\n",
      "持有\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "2019-08-14  3673.5  3653.75\n",
      "2019-08-15  3692.5  3684.75\n",
      "2019-08-16  3715.0  3694.25\n",
      "2019-08-19  3731.0  3711.75\n",
      "2019-08-20  3723.0  3719.00\n",
      "2019-08-21  3692.5  3711.75\n",
      "2019-08-22  3700.5  3711.75\n",
      "2019-08-23  3715.0  3703.75\n",
      "2019-08-26  3543.5  3622.00\n",
      "2019-08-27  3326.5  3520.75\n",
      "2019-08-28  3299.0  3421.25\n",
      "持有\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "2019-08-14  3673.5  3653.75\n",
      "2019-08-15  3692.5  3684.75\n",
      "2019-08-16  3715.0  3694.25\n",
      "2019-08-19  3731.0  3711.75\n",
      "2019-08-20  3723.0  3719.00\n",
      "2019-08-21  3692.5  3711.75\n",
      "2019-08-22  3700.5  3711.75\n",
      "2019-08-23  3715.0  3703.75\n",
      "2019-08-26  3543.5  3622.00\n",
      "2019-08-27  3326.5  3520.75\n",
      "2019-08-28  3299.0  3421.25\n",
      "2019-08-29  3291.5  3309.00\n",
      "持有\n",
      "               MA2      MA4\n",
      "date                       \n",
      "2019-08-01     NaN      NaN\n",
      "2019-08-02  3831.0      NaN\n",
      "2019-08-05  3784.5      NaN\n",
      "2019-08-06  3730.0  3780.50\n",
      "2019-08-07  3709.0  3746.75\n",
      "2019-08-08  3691.5  3710.75\n",
      "2019-08-09  3631.5  3670.25\n",
      "2019-08-12  3634.0  3662.75\n",
      "2019-08-13  3677.0  3654.25\n",
      "2019-08-14  3673.5  3653.75\n",
      "2019-08-15  3692.5  3684.75\n",
      "2019-08-16  3715.0  3694.25\n",
      "2019-08-19  3731.0  3711.75\n",
      "2019-08-20  3723.0  3719.00\n",
      "2019-08-21  3692.5  3711.75\n",
      "2019-08-22  3700.5  3711.75\n",
      "2019-08-23  3715.0  3703.75\n",
      "2019-08-26  3543.5  3622.00\n",
      "2019-08-27  3326.5  3520.75\n",
      "2019-08-28  3299.0  3421.25\n",
      "2019-08-29  3291.5  3309.00\n",
      "2019-08-30  3308.0  3303.50\n",
      "平空\n"
     ]
    }
   ],
   "source": [
    "# 5. 数据获取并推送数据\n",
    "# 获取\n",
    "df = QA.QA_fetch_get_future_day('tdx', 'RBL8', '2019-08-01', '2019-08-30')\n",
    "# 推送\n",
    "pub = publisher(exchange='x1')  # 跟订阅的Exchange一致\n",
    "for idx, item in df.iterrows():\n",
    "    pub.pub(item.to_json())  # 每行数据换成json，pub出去，上面的on_data就会收到，开始执行策略。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "margin!\n"
     ]
    }
   ],
   "source": [
    "# 6. 查看结果\n",
    "risk = QA.QA_Risk(acc)\n",
    "performance = QA.QA_Performance(acc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>datetime</th>\n",
       "      <th>code</th>\n",
       "      <th>price</th>\n",
       "      <th>amount</th>\n",
       "      <th>cash</th>\n",
       "      <th>order_id</th>\n",
       "      <th>realorder_id</th>\n",
       "      <th>trade_id</th>\n",
       "      <th>account_cookie</th>\n",
       "      <th>commission</th>\n",
       "      <th>tax</th>\n",
       "      <th>message</th>\n",
       "      <th>frozen</th>\n",
       "      <th>direction</th>\n",
       "      <th>total_frozen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-08-06 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3707.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>96659.993</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>test_local_simpledeal</td>\n",
       "      <td>3.707</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>3336.3</td>\n",
       "      <td>-2</td>\n",
       "      <td>3336.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-08-13 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3677.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>100292.616</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>test_local_simpledeal</td>\n",
       "      <td>3.677</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-08-14 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3670.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>96985.946</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>test_local_simpledeal</td>\n",
       "      <td>3.670</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>3303.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3303.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-08-21 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3686.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>100445.260</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>test_local_simpledeal</td>\n",
       "      <td>3.686</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-3</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-08-22 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3715.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>97098.045</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>test_local_simpledeal</td>\n",
       "      <td>3.715</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>3343.5</td>\n",
       "      <td>-2</td>\n",
       "      <td>3343.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-08-23 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3715.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>100437.830</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>test_local_simpledeal</td>\n",
       "      <td>3.715</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-08-26 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3372.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>97399.658</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>test_local_simpledeal</td>\n",
       "      <td>3.372</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>3034.8</td>\n",
       "      <td>-2</td>\n",
       "      <td>3034.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-08-30 00:00:00</td>\n",
       "      <td>RBL8</td>\n",
       "      <td>3350.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>100651.108</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>test_local_simpledeal</td>\n",
       "      <td>3.350</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              datetime  code   price  amount        cash order_id  \\\n",
       "0  2019-08-06 00:00:00  RBL8  3707.0    -1.0   96659.993     None   \n",
       "1  2019-08-13 00:00:00  RBL8  3677.0     1.0  100292.616     None   \n",
       "2  2019-08-14 00:00:00  RBL8  3670.0     1.0   96985.946     None   \n",
       "3  2019-08-21 00:00:00  RBL8  3686.0    -1.0  100445.260     None   \n",
       "4  2019-08-22 00:00:00  RBL8  3715.0    -1.0   97098.045     None   \n",
       "5  2019-08-23 00:00:00  RBL8  3715.0     1.0  100437.830     None   \n",
       "6  2019-08-26 00:00:00  RBL8  3372.0    -1.0   97399.658     None   \n",
       "7  2019-08-30 00:00:00  RBL8  3350.0     1.0  100651.108     None   \n",
       "\n",
       "  realorder_id trade_id         account_cookie  commission  tax message  \\\n",
       "0         None     None  test_local_simpledeal       3.707    0    None   \n",
       "1         None     None  test_local_simpledeal       3.677    0    None   \n",
       "2         None     None  test_local_simpledeal       3.670    0    None   \n",
       "3         None     None  test_local_simpledeal       3.686    0    None   \n",
       "4         None     None  test_local_simpledeal       3.715    0    None   \n",
       "5         None     None  test_local_simpledeal       3.715    0    None   \n",
       "6         None     None  test_local_simpledeal       3.372    0    None   \n",
       "7         None     None  test_local_simpledeal       3.350    0    None   \n",
       "\n",
       "   frozen  direction  total_frozen  \n",
       "0  3336.3         -2        3336.3  \n",
       "1     0.0          3           0.0  \n",
       "2  3303.0          2        3303.0  \n",
       "3     0.0         -3           0.0  \n",
       "4  3343.5         -2        3343.5  \n",
       "5     0.0          3           0.0  \n",
       "6  3034.8         -2        3034.8  \n",
       "7     0.0          3           0.0  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "acc.history_table  # 交易记录"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from '/opt/conda/lib/python3.8/site-packages/matplotlib/pyplot.py'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "risk.plot_assets_curve()  # 资产曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sell_date</th>\n",
       "      <th>buy_date</th>\n",
       "      <th>amount</th>\n",
       "      <th>sell_price</th>\n",
       "      <th>buy_price</th>\n",
       "      <th>rawdirection</th>\n",
       "      <th>unit</th>\n",
       "      <th>pnl_ratio</th>\n",
       "      <th>pnl_money</th>\n",
       "      <th>hold_gap</th>\n",
       "      <th>if_buyopen</th>\n",
       "      <th>openprice</th>\n",
       "      <th>opendate</th>\n",
       "      <th>closeprice</th>\n",
       "      <th>closedate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RBL8</th>\n",
       "      <td>2019-08-06</td>\n",
       "      <td>2019-08-13</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3707.0</td>\n",
       "      <td>3677.0</td>\n",
       "      <td>sell</td>\n",
       "      <td>10</td>\n",
       "      <td>0.008159</td>\n",
       "      <td>300.0</td>\n",
       "      <td>7 days</td>\n",
       "      <td>False</td>\n",
       "      <td>3707.0</td>\n",
       "      <td>2019-08-06 00:00:00</td>\n",
       "      <td>3677.0</td>\n",
       "      <td>2019-08-13 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RBL8</th>\n",
       "      <td>2019-08-21</td>\n",
       "      <td>2019-08-14</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3686.0</td>\n",
       "      <td>3670.0</td>\n",
       "      <td>buy</td>\n",
       "      <td>10</td>\n",
       "      <td>0.004360</td>\n",
       "      <td>160.0</td>\n",
       "      <td>7 days</td>\n",
       "      <td>True</td>\n",
       "      <td>3670.0</td>\n",
       "      <td>2019-08-14 00:00:00</td>\n",
       "      <td>3686.0</td>\n",
       "      <td>2019-08-21 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RBL8</th>\n",
       "      <td>2019-08-22</td>\n",
       "      <td>2019-08-23</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3715.0</td>\n",
       "      <td>3715.0</td>\n",
       "      <td>sell</td>\n",
       "      <td>10</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1 days</td>\n",
       "      <td>False</td>\n",
       "      <td>3715.0</td>\n",
       "      <td>2019-08-22 00:00:00</td>\n",
       "      <td>3715.0</td>\n",
       "      <td>2019-08-23 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RBL8</th>\n",
       "      <td>2019-08-26</td>\n",
       "      <td>2019-08-30</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3372.0</td>\n",
       "      <td>3350.0</td>\n",
       "      <td>sell</td>\n",
       "      <td>10</td>\n",
       "      <td>0.006567</td>\n",
       "      <td>220.0</td>\n",
       "      <td>4 days</td>\n",
       "      <td>False</td>\n",
       "      <td>3372.0</td>\n",
       "      <td>2019-08-26 00:00:00</td>\n",
       "      <td>3350.0</td>\n",
       "      <td>2019-08-30 00:00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      sell_date   buy_date  amount  sell_price  buy_price rawdirection  unit  \\\n",
       "code                                                                           \n",
       "RBL8 2019-08-06 2019-08-13     1.0      3707.0     3677.0         sell    10   \n",
       "RBL8 2019-08-21 2019-08-14     1.0      3686.0     3670.0          buy    10   \n",
       "RBL8 2019-08-22 2019-08-23     1.0      3715.0     3715.0         sell    10   \n",
       "RBL8 2019-08-26 2019-08-30     1.0      3372.0     3350.0         sell    10   \n",
       "\n",
       "      pnl_ratio  pnl_money hold_gap  if_buyopen  openprice  \\\n",
       "code                                                         \n",
       "RBL8   0.008159      300.0   7 days       False     3707.0   \n",
       "RBL8   0.004360      160.0   7 days        True     3670.0   \n",
       "RBL8   0.000000        0.0   1 days       False     3715.0   \n",
       "RBL8   0.006567      220.0   4 days       False     3372.0   \n",
       "\n",
       "                 opendate  closeprice            closedate  \n",
       "code                                                        \n",
       "RBL8  2019-08-06 00:00:00      3677.0  2019-08-13 00:00:00  \n",
       "RBL8  2019-08-14 00:00:00      3686.0  2019-08-21 00:00:00  \n",
       "RBL8  2019-08-22 00:00:00      3715.0  2019-08-23 00:00:00  \n",
       "RBL8  2019-08-26 00:00:00      3350.0  2019-08-30 00:00:00  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "performance.pnl  # 盈利情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 7. 保存结果\n",
    "risk.save()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "acc.save()"
   ]
  }
 ],
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